Job Description
We are seeking a visionary AI Architect (2026 Vision) to lead the development of next-generation intelligent systems. At OmniStream Systems, we are building the infrastructure for tomorrow’s digital economy. In this pivotal role, you will bridge the gap between theoretical AI research and scalable production engineering.
Join our elite engineering team and help define the technological landscape of 2026 and beyond. You will work on cutting-edge projects involving generative AI, predictive analytics, and autonomous systems.
Why Join Us?
- Competitive compensation package with equity.
- Flexible work environment (Hybrid/Remote options).
- Access to the latest hardware and cloud infrastructure.
The Role:
As a Future-Ready AI Architect, you will be responsible for designing robust AI pipelines, mentoring junior engineers, and ensuring our solutions are scalable and future-proof. You will collaborate with cross-functional teams to integrate AI solutions into core business products.
Responsibilities
- Design & Architecture: Architect end-to-end AI/ML pipelines that scale efficiently to millions of users.
- Model Optimization: Fine-tune and optimize large language models and neural networks for real-time inference.
- Future-Proofing: Evaluate emerging technologies (e.g., Agentic AI, Quantum-ready algorithms) to ensure our stack remains relevant in 2026.
- Team Leadership: Lead code reviews, technical design sessions, and best practices implementation for the AI squad.
- Deployment: Manage the deployment of models on cloud platforms (AWS/GCP) using Kubernetes and Docker.
- Innovation: Conduct research on novel algorithms to solve complex business problems.
Qualifications
- Education: Master’s degree in Computer Science, Artificial Intelligence, or a related technical field (PhD preferred).
- Experience: 5+ years of experience in software engineering, with at least 3 years focused on Machine Learning and AI.
- Programming: Expert proficiency in Python, TensorFlow, PyTorch, or JAX.
- Systems: Deep understanding of distributed systems, cloud architecture, and MLOps practices.
- Soft Skills: Excellent communication skills and the ability to translate technical concepts for non-technical stakeholders.
- Tools: Experience with version control (Git), CI/CD, and containerization.